# Development Methodology The required breadth of material property data needed for the development of universal ML system for predicting material properties can be in principle obtained from a large database containing structural material properties, such as Total Materia Horizon \[5[^1]], which comprises more than 500,000 materials. However, there is no single ML model capable of effectively using its 20 million property records for dozens of material properties to deliver predictions of any acceptable quality. Therefore, classifying and grouping materials, normalizing their properties and conditions (a combination of thermic-, mechanical- and other processing patterns of a material), and then applying dataset splitting and division, is essential to enable effective ML on such comprehensive and diversified datasets. [^1]: Total Materia AG: [www.totalmateria.com](http://www.totalmateria.com), accessed July 2022 --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.totalmateria.com/predictor/predictor-2-whitepaper/development-methodology.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.